MicroRNAs (miRs) are small non-coding RNA molecules that are directly involved in regulation of gene expression. Their mechanism relies on complementary sequence between each miR and its mRNA target. Many lines of evidence indicate the involvement of miRs in human disease, particularly in neurological disorders. The long-term objective of this application is to better understand the role of genetic variation in miRs in neurological disorders. Currently, there is no systematic analysis of miRs that provides a way to determine the disease relevance of variants in different miR or miR-target sequences. Here, we will develop and subsequently apply a method that ranks brain-expressed miRs by their likelihood of carrying disease causing mutations. The central hypothesis of this application is that certain miRs, and by extension their associated targets, are more or less likely to carry disease causing mutations than others, and that these can be discriminated by integrated population genetic data and conservation data. This hypothesis will be tested by pursuing the following specific aims: (1) Rank brain-expressed miRs by their relative tolerance to variation, and; (2) Identify candidate disease-causal miRs in neurological disorders. Upon completion, this application will provide a novel way to detect causal variants in neurological disorders and a better understanding of the mechanisms of neurological disorders. Additionally, the findings from this application could help identify new strategies for the development of treatments for these diseases.